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Supercapacitor Parameter Estimation and Hybridyzation with PEMFC for Purge Compensation

Jannif, Nayzel I. and Ram, Krishnil R. and Bangalini, Kaluwin and Loli, Andrea and Mohammadi, Ali and Cirrincione, Maurizio (2022) Supercapacitor Parameter Estimation and Hybridyzation with PEMFC for Purge Compensation. [Conference Proceedings]

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Abstract

This paper focuses on the hybridization of a Proton Exchange Membrane Fuel Cell (PEMFC) and a Supercapacitor to smoothen the voltage disturbance caused by purging in the Fuel Cell. Firstly, a two-branch supercapacitor (SC) model is implemented in Simulink. The parameters of the SC are estimated using Genetic Algorithm Optimization and compared with the classical Faranda method. There is good agreement with the results generated using the Genetic Algorithm Optimization approach. Additionally, experiments were carried out on a 1.2kW PEMFC to acquire the voltage data. Voltage drops during purge were measured and used with the PEMFC model to simulate purge behaviour in the fuel cell. The SC was then connected in parallel to the PEMFC to smoothen the voltage output. The work is still in progress, and so far, positive results have been achieved where the SC has been effective in negating the effects of purge phenomena in PEMFC.

Item Type: Conference Proceedings
Uncontrolled Keywords: Fuel Cell, Supercapacitor, Hybrid Systems, Parameter Estimation, Genetic Algorithm, Purge, PEMFC
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: School of Information Technology, Engineering, Mathematics and Physics (STEMP)
Depositing User: Nayzel Jannif
Date Deposited: 07 Oct 2022 05:46
Last Modified: 07 Oct 2022 05:46
URI: https://repository.usp.ac.fj/id/eprint/13733

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